How to Improve Conversion Rate with AI-Powered Marketing

An AI-generated image of a female CRM marketer browsing her client's profile chart on a computer screen.
Image generated using DALL-E

Customer conversion rate is a pivotal metric for measuring business growth in CRM marketing, yet it often remains challenging for marketers.

However, with the inception of AI technology, the landscape of customer conversion in CRM marketing is undergoing a rapid transformation. A study in 2022 foresaw AI in the CRM market is expected to grow from USD 7.9 Billion in 2020 to USD 25.5 Billion by 2025, at a CAGR of 26.2%.

But how exactly is AI transforming traditional methods, and what specific AI-powered tools and techniques are driving this change? Today’s article will explore how AI improves customer conversion rates for businesses in CRM marketing.

1. Predictive Lead Scoring

Predictive lead scoring aims to predict the timing of customer purchases and determine whether they are suitable for the brand from the early stages.

AI-powered CRM systems employ predictive lead-scoring models to analyze vast amounts of data and identify users with the highest potential to convert into customers.

Companies that have used AI-based customer targeting have seen an increase of 9%-20% in marketing conversions and a 13%-31% decrease in churn rates.

This means that AI-powered CRM allows companies to identify at-risk customers sooner and take action before it’s too late.

By leveraging machine learning and Natural Language Processing (NLP), AI-powered solutions can effectively sort out existing data, identify patterns, and prioritize users based on their likelihood to convert.

This allows your CRM marketers to focus on prospects challenging likely to make the next purchase, thereby increasing efficiency and closing rates.

2. Hyper-personalized Outreach

If AI represents a breakthrough in technology, personalization is its killer slogan. And we believe the same slogan can apply to CRM marketing as well.

AI-powered tools have developed to the extent that they now allow businesses to deliver personalized outreach at scale, tailoring communication to leads' unique needs and interests. This results in the acquisition of loyal, long-term customers.

Through advanced algorithms, conversational AI like ChatGPT can increase customer interactions and enhance journey mapping. It can help sales managers analyze customer data to craft personalized email messages that resonate with each prospect.

When executed at proper timing, personalized messages deliver eight times higher ROI on marketing spend and increase sales by 10% or more.

3. Data Enrichment and Segmentation

Have you ever struggled to understand vast data of potential customers, fearing the data might lead you nowhere? This is a common frustration shared by many CRM marketers in the industry.

Using AI technology, CRM marketing solutions can automatically classify vast customer data and easily derive valuable insights.

Furthermore, by analyzing customer data from various sources, such as push notifications, emails, and website visits, and supplementing the CRM database, marketers can effortlessly refer to it in the future. This shows how vital the role of data science is in CRM marketing.

Ultimately, an enhanced database is a foundation for marketers to effectively target specific customer groups by segmenting them based on behavior, preferences, and demographics.

Final Thoughts

Undoubtedly, AI enhances customer conversion rates for businesses that leverage CRM marketing by identifying and engaging potential customers more effectively than ever before.

But AI-powered CRM has key milestones to cover before finally settling as a reliable service. There are data privacy and ethical implications of AI to consider, and digital CRM relies heavily on data, not just the volume of data gathered but also its quality, which can only be achieved through advanced analysis and interpretation techniques.

The good news is that the CRM industry is actively working to ensure that AI-driven CRM solutions prioritize customer privacy and meet evolving technical demands. This will foster trust between businesses and their customers, benefiting both parties.

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